Weissmann, T.; Mansoorian, S.; May, M.S.; Lettmaier, S.; Höfler, D.; Deloch, L.; Speer, S.; Balk, M.; Frey, B.; Gaipl, U.S.;
et al. Deep Learning and Registration-Based Mapping for Analyzing the Distribution of Nodal Metastases in Head and Neck Cancer Cohorts: Informing Optimal Radiotherapy Target Volume Design. Cancers 2023, 15, 4620.
https://doi.org/10.3390/cancers15184620
AMA Style
Weissmann T, Mansoorian S, May MS, Lettmaier S, Höfler D, Deloch L, Speer S, Balk M, Frey B, Gaipl US,
et al. Deep Learning and Registration-Based Mapping for Analyzing the Distribution of Nodal Metastases in Head and Neck Cancer Cohorts: Informing Optimal Radiotherapy Target Volume Design. Cancers. 2023; 15(18):4620.
https://doi.org/10.3390/cancers15184620
Chicago/Turabian Style
Weissmann, Thomas, Sina Mansoorian, Matthias Stefan May, Sebastian Lettmaier, Daniel Höfler, Lisa Deloch, Stefan Speer, Matthias Balk, Benjamin Frey, Udo S. Gaipl,
and et al. 2023. "Deep Learning and Registration-Based Mapping for Analyzing the Distribution of Nodal Metastases in Head and Neck Cancer Cohorts: Informing Optimal Radiotherapy Target Volume Design" Cancers 15, no. 18: 4620.
https://doi.org/10.3390/cancers15184620
APA Style
Weissmann, T., Mansoorian, S., May, M. S., Lettmaier, S., Höfler, D., Deloch, L., Speer, S., Balk, M., Frey, B., Gaipl, U. S., Bert, C., Distel, L. V., Walter, F., Belka, C., Semrau, S., Iro, H., Fietkau, R., Huang, Y., & Putz, F.
(2023). Deep Learning and Registration-Based Mapping for Analyzing the Distribution of Nodal Metastases in Head and Neck Cancer Cohorts: Informing Optimal Radiotherapy Target Volume Design. Cancers, 15(18), 4620.
https://doi.org/10.3390/cancers15184620
